SBHacksXI/tutorial.py at main · Alexander-Reyes9/SBHacksXI · GitHub

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#
# Beat tracking example
#import librosa

# 1. Get the file path to an included audio example
#filename = librosa.example('nutcracker')


# 2. Load the audio as a waveform `y`
#    Store the sampling rate as `sr`
#y, sr = librosa.load(filename)

# 3. Run the default beat tracker
#tempo, beat_frames = librosa.beat.beat_track(y=y, sr=sr)

#print('Estimated tempo: {:.2f} beats per minute'.format(float(tempo)))

# 4. Convert the frame indices of beat events into timestamps
#beat_times = librosa.frames_to_time(beat_frames, sr=sr)


# Code source: Stefan Balke
# License: ISC
# sphinx_gallery_thumbnail_number = 4

import numpy as np
import matplotlib
import matplotlib.pyplot as plt

import librosa


x_1, fs = librosa.load('audio/sir_duke_slow.ogg')
# And a second version, slightly faster.
x_2, fs = librosa.load('audio/sir_duke_fast.ogg')

fig, ax = plt.subplots(nrows=2, sharex=True, sharey=True)
librosa.display.waveshow(x_1, sr=fs, ax=ax[0])
ax[0].set(title='Slower Version $X_1$')
ax[0].label_outer()

librosa.display.waveshow(x_2, sr=fs, ax=ax[1])
ax[1].set(title='Faster Version $X_2$')

hop_length = 1024

x_1_chroma = librosa.feature.chroma_cqt(y=x_1, sr=fs,
                                         hop_length=hop_length)
x_2_chroma = librosa.feature.chroma_cqt(y=x_2, sr=fs,
                                         hop_length=hop_length)

fig, ax = plt.subplots(nrows=2, sharey=True)
img = librosa.display.specshow(x_1_chroma, x_axis='time',
                               y_axis='chroma',
                               hop_length=hop_length, ax=ax[0])
ax[0].set(title='Chroma Representation of $X_1$')
librosa.display.specshow(x_2_chroma, x_axis='time',
                         y_axis='chroma',
                         hop_length=hop_length, ax=ax[1])
ax[1].set(title='Chroma Representation of $X_2$')
fig.colorbar(img, ax=ax)

D, wp = librosa.sequence.dtw(X=x_1_chroma, Y=x_2_chroma, metric='cosine')
wp_s = librosa.frames_to_time(wp, sr=fs, hop_length=hop_length)

fig, ax = plt.subplots()
img = librosa.display.specshow(D, x_axis='time', y_axis='time', sr=fs,
                               cmap='gray_r', hop_length=hop_length, ax=ax)
ax.plot(wp_s[:, 1], wp_s[:, 0], marker='o', color='r')
ax.set(title='Warping Path on Acc. Cost Matrix $D$',
       xlabel='Time $(X_2)$', ylabel='Time $(X_1)$')
fig.colorbar(img, ax=ax)